《语音线性预测编码》PPT课件

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1、SpeechSignalProcessing—Lecture10LinearPredictiveCoding(LPC)-Introduction1LPCMethodsLPCmethodsarethemostwidelyusedinspeechcoding,speechsynthesis,speechrecognition,speakerrecognitionandverificationandforspeechstorageLPCmethodsprovideextremelyaccurateestimatesofsp

2、eechparameters,anddoesitextremelyefficientlybasicideaofLinearPrediction:currentspeechsamplecanbecloselyapproximatedasalinearcombinationofpastsamples,i.e.,2LPCMethods3BasicPrinciplesofLPH(z)4LPBasicEquations5LPEstimationIssues6Solutionfor{αk}7Solutionfor{αk}8Sol

3、utionfor{αk}9Solutionfor{αk}10AutocorrelationMethod11AutocorrelationMethod12AutocorrelationMethod13CovarianceMethod14CovarianceMethod15CholeskyDecompositionExample16CholeskyDecomposition17CholeskyDecompositionExample18CovarianceMethodMinimumError19SolutiontoAut

4、ocorrelationMethod20AutocorrelationExample21ComparisonsBetweenLPMethodsthevariousLPsolutiontechniquescanbecomparedinanumberofways,includingthefollowing:computationalissuesnumericalissuesstabilityofsolutionnumberofpoles(orderofpredictor)window/sectionlengthforan

5、alysis22LPSolutionComputationsassumeN1≈N2>>p;choosevaluesofN1=300,N2=300,p=10computationforcovariancemethod≈N1p+p3≈4000*,+autocorrelationmethod≈N2p+p2≈3100*,+23LPSolutionComparisonsstabilityguaranteedforautocorrelationmethodcannotbeguaranteedforcovariancemethod

6、;aswindowsizegetslarger,thisalmostalwaysmakesthesystemstablechoiceofLPanalysisparametersneed2poles(for1kHz)foreachvocaltractresonancebelowFs/2need3-4polestorepresentsourceshapeandradiationloadusevaluesofp≈13-1424PredictionErrorSignalBehavior25LPAnalysisofSpeech

7、noteerrorsignalneartime=0forautocorrelationmethod26FrequencyDomainInterpretation27FrequencyDomainInterpretation28FrequencyDomainInterpretation29ComparisonsofSpectralAnalysisMethodsSpectralComparisonsacrossMethodsa:narrowbandanalysis—resolvespitchharmonicsb:wide

8、bandanalysis—givesasmoothedspectrumc:homomorphicsmoothing—givesgoodindicationsofformantlocationsd:LPCfitwithp=12—formantsandbandwidthscanreadilybeobtainedbyfactoringLPCpolyn